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12/08/2020
2-Step Sparse-View CT Reconstruction with a Domain-Specific Perceptual Network
Computed tomography is widely used to examine internal structures in a n...
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11/12/2020
Disassemblable Fieldwork CT Scanner Using a 3D-printed Calibration Phantom
The use of computed tomography (CT) imaging has become of increasing int...
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11/19/2019
Projection-to-Projection Translation for Hybrid X-ray and Magnetic Resonance Imaging
Hybrid X-ray and magnetic resonance (MR) imaging promises large potentia...
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10/18/2019
The TCGA Meta-Dataset Clinical Benchmark
Machine learning is bringing a paradigm shift to healthcare by changing ...
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09/14/2019
Torchmeta: A Meta-Learning library for PyTorch
The constant introduction of standardized benchmarks in the literature h...
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07/03/2019
Learning with Known Operators reduces Maximum Training Error Bounds
We describe an approach for incorporating prior knowledge into machine l...
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07/09/2018
Deriving Neural Network Architectures using Precision Learning: Parallel-to-fan beam Conversion
In this paper, we derive a neural network architecture based on an analy...
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06/28/2018
Adversarial and Perceptual Refinement for Compressed Sensing MRI Reconstruction
Deep learning approaches have shown promising performance for compressed...
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04/11/2018
Projection image-to-image translation in hybrid X-ray/MR imaging
The potential benefit of hybrid X-ray and MR imaging in the intervention...
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01/12/2018
Deep Learning for Sampling from Arbitrary Probability Distributions
This paper proposes a fully connected neural network model to map sample...
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12/01/2017
Precision Learning: Towards Use of Known Operators in Neural Networks
In this paper, we consider the use of prior knowledge within neural netw...
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11/09/2017
Frangi-Net: A Neural Network Approach to Vessel Segmentation
In this paper, we reformulate the conventional 2-D Frangi vesselness mea...
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10/20/2017
MR to X-Ray Projection Image Synthesis
Hybrid imaging promises large potential in medical imaging applications....
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10/17/2017